Drone reference tracking in a non-inertial frame: control, design and experiment

Abstract

Drones and mobile robots in general experience motion sickness when put inside a GPS denied moving environment. This navigation problem is of a novel nature and barely explored in the literature. The objective of this paper is to design a control strategy for drone reference tracking inside the moving environment. First, we provide an initial formulation of the problem where the non-inertial frame is assumed to have only a translation motion relative to the inertial reference frame. Then we derive the dynamic model of the drone in the non-inertial frame using the relative motion principle. After that, we use a combined Sliding mode controller and Extended Kalman Filter with Unknown Inputs (EKF-UI) for trajectory tracking. The EKF-UI enables to jointly estimates the states of the drone and the non-inertial frame accelerations. The sliding mode control laws are computed using the measured and estimated states to ensure the asymptotic convergence of the whole observer-based control strategy. The performance of the proposed observer-based control strategy is tested through simulation and experiment.